Circuit system health condition prediction method based on low-frequency noise and deep learning

The invention relates to a circuit system health condition prediction method based on low-frequency noise and deep learning, and the method comprises the following steps: 1, carrying out the stability importance distribution of a circuit system; 2, extracting low-frequency noise, and obtaining steady-state distribution characteristic parameters of low-frequency noise time domain analysis noise of the component; 3, processing low-frequency noise signal data, and establishing a neural network model; and step 4, training of the neural network model is completed, and a prediction result of the circuit life is obtained. A deep learning prediction model is established through analysis of low-frequency noise of components, circuit health condition analysis is achieved, the method can adapt to circuit systems with different failure criteria, the method is suitable for accurate diagnosis in the engineering field, and compared with a traditional aging test method based on modeling of a large number of test results, the